IBM InfoSphere QualityStage vs. SAS Data Management

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
IBM InfoSphere QualityStage
Score 9.5 out of 10
N/A
IBM InfoSphere QualityStage is a data quality offering from IBM.N/A
SAS Data Management
Score 8.0 out of 10
N/A
A suite of solutions for data connectivity, enhanced transformations and robust governance. Solutions provide a unified view of data with access to data across databases, data warehouses and data lakes. Connects with cloud platforms, on-premises systems and multicloud data sources.N/A
Pricing
IBM InfoSphere QualityStageSAS Data Management
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
IBM InfoSphere QualityStageSAS Data Management
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
IBM InfoSphere QualityStageSAS Data Management
Features
IBM InfoSphere QualityStageSAS Data Management
Data Quality
Comparison of Data Quality features of Product A and Product B
IBM InfoSphere QualityStage
8.1
2 Ratings
4% below category average
SAS Data Management
-
Ratings
Data source connectivity9.02 Ratings00 Ratings
Data profiling7.42 Ratings00 Ratings
Master data management (MDM) integration8.02 Ratings00 Ratings
Data element standardization8.02 Ratings00 Ratings
Match and merge7.32 Ratings00 Ratings
Address verification9.02 Ratings00 Ratings
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
IBM InfoSphere QualityStage
-
Ratings
SAS Data Management
8.3
10 Ratings
2% above category average
Connect to traditional data sources00 Ratings8.610 Ratings
Connecto to Big Data and NoSQL00 Ratings8.19 Ratings
Data Transformations
Comparison of Data Transformations features of Product A and Product B
IBM InfoSphere QualityStage
-
Ratings
SAS Data Management
6.7
8 Ratings
18% below category average
Simple transformations00 Ratings6.18 Ratings
Complex transformations00 Ratings7.48 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
IBM InfoSphere QualityStage
-
Ratings
SAS Data Management
6.7
8 Ratings
15% below category average
Data model creation00 Ratings5.56 Ratings
Metadata management00 Ratings7.47 Ratings
Business rules and workflow00 Ratings6.67 Ratings
Collaboration00 Ratings7.07 Ratings
Testing and debugging00 Ratings6.17 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
IBM InfoSphere QualityStage
-
Ratings
SAS Data Management
7.9
9 Ratings
0% above category average
Integration with data quality tools00 Ratings7.69 Ratings
Integration with MDM tools00 Ratings8.27 Ratings
Best Alternatives
IBM InfoSphere QualityStageSAS Data Management
Small Businesses
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Score 8.1 out of 10
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Score 10.0 out of 10
Medium-sized Companies
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.0 out of 10
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.0 out of 10
Enterprises
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.0 out of 10
IBM InfoSphere Information Server
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Score 8.0 out of 10
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User Ratings
IBM InfoSphere QualityStageSAS Data Management
Likelihood to Recommend
9.0
(2 ratings)
7.6
(11 ratings)
Likelihood to Renew
-
(0 ratings)
9.0
(2 ratings)
Usability
-
(0 ratings)
6.0
(2 ratings)
Performance
-
(0 ratings)
9.0
(1 ratings)
Support Rating
-
(0 ratings)
7.7
(6 ratings)
User Testimonials
IBM InfoSphere QualityStageSAS Data Management
Likelihood to Recommend
IBM
Standardization of data using rules for names and addresses. Possibility of building our own rules to standardize other data. Contruction of complex rules of matching and consolidation of data. Native integration with ETL tools and data governance.
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SAS
When data is in a system that needs a complex transformation to be usable for an average user. Such tasks as data residing in systems that have very different connection speeds. It can be integrated and used together after passing through the SAS Data Integration Studio removing timing issues from the users' worries. A part that is perhaps less appropriate is getting users who are not familiar with the source data to set up the load processes.
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Pros
IBM
  • Create rules
  • Standardization and normalization of data
  • Integration with DataStage
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SAS
  • SAS/Access is great for manipulating large and complex databases.
  • SAS/Access makes it easy to format reports and graphics from your data.
  • Data Management and data storage using the Hadoop environment in SAS/Access allows for rapid analysis and simple programming language for all your data needs.
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Cons
IBM
  • Should include all the data profiling functionality
  • Better features to tune matching capability
  • Include AI to automatically recommend actions to improve processes
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SAS
  • Requires third-party drivers to connect to common data sources like SFDC, MS SQL, Postgres.
  • Debugging errors from the logs is a complicated process.
  • E-mail alert system is very primitive and needs customization to make it more modern,
  • Cannot send SMS alerts for jobs.
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Likelihood to Renew
IBM
No answers on this topic
SAS
We are happy with the software and its functionality. As a SAS-shop, DataFlux is a logical choice for complex data integration.
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Usability
IBM
No answers on this topic
SAS
The main negative point is the use of a non-standard language for customizations, as well as the poor integration with non-SAS systems. However, there is no doubt that it is a high-performance and powerful product capable of responding optimally to certain requirements.
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Performance
IBM
No answers on this topic
SAS
It worked as expected.
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Support Rating
IBM
No answers on this topic
SAS
With SAS, you pay a license fee annually to use this product. Support is incredible. You get what you pay for, whether it's SAS forums on the SAS support site, technical support tickets via email or phone calls, or example documentation. It's not open source. It's documented thoroughly, and it works.
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Alternatives Considered
IBM
It is a robust tool. It can be integrated with several DB. It works very well with DS. You can create your rules, and define the percentage of standardization or normalization
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SAS
Because of ease of using SAS DI and data processing speed. There were lots of issues with AWS Redshift on cloud environment in terms of making connections with the data sources and while fetching the data we need to write complex queries.
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Return on Investment
IBM
  • Improving Data Quality
  • Reducing costs due to better Data Quality
  • Single view of customer / product
  • Better data governance
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SAS
  • We have more users who can connect to the many different data sources.
  • Our users do have existing SAS programming knowledge and that can carry over.
  • Business functions are starting to rely on SAS Data Integration Studio work product shortly after introduction.
Read full review
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